Now that subsurface imaging has become so sophisticated and levels of detail unimaginable in the past are routinely available, it is tempting to think that these tools are all we need to understand the geology of an area. So where is the value of field-based training to the industry? Has it become a luxury?
A degree in geology used to provide a reliable grounding in fieldwork: at one time there was a notional benchmark that an honours degree course in the UK would include about 100 days of fieldwork. In many UK university geoscience departments lack of funding has threatened to diminish the role that fieldwork plays in the training of students. More worryingly there also seems to be a diminishing number of academic staff who are experienced field geologists. Funding for field-based research has decreased, so many academics have a lab-based focus in their research and do not necessarily have extensive field experience to pass on. Consequently geoscientists coming into the oil and gas industry from UK universities are likely to have less field experience than those of a decade or two ago. Does this matter?
The old aphorism ‘the best geologist is the one who has seen the most rocks’ is often presented to justify training geoscientists through fieldwork – but why should this be the case? What exactly is experienced in the field that cannot be experienced from examining samples in a lab or viewing images on a computer screen?
Context at a Continuum of Scales
Probably the most important thing that field observation alone can provide is this – ‘context at a continuum of scales’. It is only at a rock-face that it is possible to go from looking at grains of sand less than a millimetre across, to views of the regional geology that may stretch for tens of kilometres, while potentially seeing everything in between across those seven or more orders of magnitude. Whilst it is only in places of spectacular exposure that this is possible, these are the very places where field training is best carried out: in the shoreface sandstones of the Book Cliffs of Utah, the fold and thrust belt of the Southern Pyrenees and the whole systems tracts exposed in the fjords of Spitsbergen.
There is a spatial resolution gap in the range of scales of observation within subsurface data. At the smaller scales, microscopic levels of analysis are available from cuttings and core samples, with core providing detail of features such as vertical trends. These analyses overlap with well logs, which are typically more vertically continuous and with vertical resolution in conventional logs in the order of tens of centimetres. At the other end of the scale, seismic data provides the broader context with both vertical and horizontal resolution measured in tens of metres.
In between lies a gap: a gap in which resolution in three dimensions at the scale of metres is not available from subsurface data alone. And as this is the scale at which reservoir models are built we need to have means to integrate between seismic and well-based data. Since this is not currently possible using subsurface data alone, we need to use our understanding of relationships observed in the field to integrate and interpolate, as demonstrated in the two examples that follow.
When Only Field Observation Will Do
Example 1: Fluvial successions
The photograph below is of outcrops of fluvial sandstones in the Miocene of the Ebro Basin in Northern Spain. There is considerable heterogeneity at scales ranging from centimetres to tens of metres, and because of the lateral variability any single vertical section would not be representative of the succession as a whole. This cliff is less than 100m high, so none of the complexity would be discernible on a seismic reflection profile. If presented with a unit composed of sediments deposited by deposition in river channels and on overbanks, the only way to create a model is to use an understanding of the range of geometries and relationships seen in the field.
To build a credible model it is vital to apply the knowledge of the characteristics of fluvial strata gained not just from one field example, but from multiple field case studies. Observations of field examples will clearly demonstrate that reservoir models built from shoestring sandstones are not a realistic reflection of how most fluvial successions appear in real life. The shoe-string model is based on a fundamental misconception that river channel deposits directly reflect the planform of a river channel; they don’t – rivers deposit when they laterally migrate and create sandstone complexes that are sheets or linear features significantly wider than the channel.
In the case of the succession seen in the example above, the behaviour of a gas reservoir with apparently low net-to-gross can only be understood when it is realised that the thin sheet sandstones deposited on the floodplain provide connection between the coarser, thicker channel sandstone bodies. That understanding could not be reached from core, well-log or seismic data.
Put simply, it is not possible to create either a conceptual model or a reservoir model of a fluvial succession without having seen similar rocks in the field.
Example 2: Internal fault architecture and fault sealing
All too often subsurface maps depict faults as a single plane – the reality is that faults are complex three-dimensional structures with much internal heterogeneity and are better thought of as fault zones. The scale-independent or ‘fractal’ nature of faults means that observation of faults at outcrop can provide critical insights into their internal structure in the subsurface and their potential to act as reservoir seals or baffles in oil and gas fields.
The figure below shows a normal fault developed in a heterolithic late Miocene succession of shoreface sandstones and interbedded marine shales. Close inspection of this fault zone (also shown) reveals a highly complex internal structure composed of lenses of intact stratigraphy bounded by anastomosing slip planes with or without shale smear. It is relatively easy to trace a path, albeit a rather tortuous one, across the fault in 2D that does not cross any shale smear, implying that the fault will not seal. This simple field observation of a potentially leaky fault has important consequences at a prospect scale.
Whilst such complex and 3D aspects of faults can be taught in the classroom, it is only in the field that the real implications of these features of fault zones can be effectively demonstrated. The deeper understanding and insights gained from such field training mean that geoscientists and reservoir engineers will critically assess techniques or software that assume certain properties for faults. As a result they will be in a considerably better position to quantify uncertainty associated with a given fault leaking or sealing.
The Value of Field Observations
So a few days spent studying fluvial channel bodies will help constrain the reservoir model by providing a basis for deciding whether sandstone units will be laterally extensive and connect across a field. Having a geoscientist apply calculations of shale gouge ratio/ shale smear factor after observing fault zones in the field will result in a better understanding of the potential of the fault to seal than calculations applied by someone without that practical vision.
The collection of seismic, core and well-log data is a very significant outlay and is essential to exploration and field development. However, these data do not provide all the information that is needed to build a picture of the subsurface geometry at the scale required for reservoir development. The resolution gap has to be filled and that can only be achieved by field observations that provide real examples of what does, and does not, occur in the rock record.
Field examples can be provided by training courses that visit relevant outcrops, which provide the visualisation of comparable relationships. Alternatively, carrying out original observations of selected analogues can provide bespoke data and understanding to address a particular situation. In either case the rocks observed in the field are an essential reality check on any model for a subsurface relationship.
Admittedly we are biased: we are field geologists and we have spent our careers making field observations and being involved in running field-based training courses. There is a cost in time and money to geological fieldwork, but we are bound to ask the question – can you afford not to do it?